Spatial variability and correlation of soybean yield components and harvest losses

Anna Kelly Severino Santos; Jorge Wilson Cortez

doi:10.18011/bioeng.2025.v19.1261

Authors

Anna Kelly Severino Santos Faculty of Agricultural Sciences, Federal University of Grande Dourados (FCA/UFGD), Dourados/MS, Brazil https://orcid.org/0000-0001-7706-7367
Jorge Wilson Cortez Faculty of Agricultural Sciences, Federal University of Grande Dourados (FCA/UFGD), Dourados/MS, Brazil https://orcid.org/0000-0003-1120-719X

DOI:

https://doi.org/10.18011/bioeng.2025.v19.1261

Keywords:

Precision agriculture, NDVI, Soybean yield

Abstract

The spatial variability of yield components and harvest losses represents a determining factor for production efficiency in agricultural systems managed under the principles of precision agriculture. In this context, the present study aimed to evaluate the spatial variability of soybean yield components and harvest losses, as well as to investigate their relationship with the Normalized Difference Vegetation Index (NDVI). The study was conducted on a commercial farm in two production fields with areas of 70.46 ha and 63.14 ha. A regular sampling grid was established with the addition of 20% random points, totaling 82 sampling points per field. The variables analyzed were NDVI, plant height, first pod insertion height, grain yield, and harvest losses, classified as pre-harvest losses, total losses, and harvester losses. The data were subjected to descriptive statistical analysis, geostatistical analysis, spatial interpolation, and Pearson correlation. The results showed spatial variability for NDVI, plant height, first pod insertion height, and yield. The mean yield was 2846.2 kg ha⁻¹ in field T1 and 4402.5 kg ha⁻¹ in field T2. A positive correlation between NDVI and yield was observed in field T1. Total grain losses were above the acceptable limit of 60 kg ha⁻¹, ranging predominantly between 300 and 600 kg ha⁻¹ (6.81 to 13.63% of production), with regions reaching 600 to 1200 kg ha⁻¹ (13.63 to 27.26%). A strong relationship between harvester losses and total losses was also found, highlighting the influence of harvester adjustment and operating conditions on harvest efficiency.

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